System and method for intraoperative detection of cancer margins using conformal filters in a dual polarization configuration

ABSTRACT

Devices, systems, and methods for distinguishing tissue types are described herein. Such devices and systems may use dual polarization, conformal filters to acquire image data from target tissues and a processor to create an image in which the contrast between tissues has been enhanced.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the priority benefit of U.S. Provisional PatentApplication No. 61/833,622, filed Jun. 11, 2013 and entitled “System andMethod for Intraoperative Detection of Cancer Margins Using ConformalFilters in a Dual Polarization Configuration,” the contents of which areincorporated herein by reference in its entirety.

BACKGROUND

Spectroscopic imaging combines digital imaging and molecularspectroscopy techniques including Raman scattering, fluorescence,photoluminescence, ultraviolet, visible and infrared absorptionspectroscopies. When such techniques are applied to the chemicalanalysis of materials, spectroscopic imaging is commonly referred to aschemical imaging or molecular imaging. Instruments for performingspectroscopic, e.g. chemical, imaging typically comprise an illuminationsource, an image gathering optic, a focal plane array imaging detectorand an image spectrometer.

Generally, the sample size determines the choice of image gatheringoptic. For example, a microscope is typically employed to analyzesub-micron to millimeter spatial dimension samples. In the case oflarger objects, in the range of millimeter to meter dimensions,macro-lens optics are appropriate. For samples located within relativelyinaccessible environments, flexible fiberscope or rigid borescopes maybe employed. Further, for very large scale objects, such as planetaryobjects, telescopes are appropriate image gathering optics.

For detection of images formed by the various optical systems,two-dimensional, imaging focal plane array (“FPA”) detectors aretypically employed. The choice of FPA detectors is governed by thespectroscopic technique employed to characterize the sample of interest.For example, silicon (Si) charge-coupled device (“CCD”) detectors orCMOS detectors are typically employed with visible wavelengthfluorescence and Raman spectroscopic imaging systems, while indiumgallium arsenide (“InGaAs”) FPA detectors are typically employed withnear-infrared spectroscopic imaging systems.

Spectroscopic imaging of a sample is commonly implemented by one of twomethods. First, point-source illumination may be used on a sample tomeasure the spectrum at each point of the illuminated area. Second,spectra can be collected over the entire area encompassing a samplesimultaneously using an electronically tunable optical imaging filtersuch as an acousto-optic tunable filter (“AOTF”), a multi-conjugatetunable filter (“MCF”), or a liquid crystal tunable filter (“LCTF”).Here, the organic material in such optical filters is actively alignedby applied voltages to produce the desired bandpass and transmissionfunction. The spectrum obtained for each pixel of an image forms acomplex data set referred to as a hyperspectral image. Hyperspectralimages may contain the intensity values at numerous wavelengths or thewavelength dependence of each pixel element in the image. Multivariateroutines, such as chemometric techniques, may be used to convert spectrato classifications.

Spectroscopic devices operate over a range of wavelengths dependent onthe operation ranges of the detectors or tunable filters employed. Thedevices may operate and provide analysis in the Ultraviolet (UV),visible (VIS), near infrared (NIR), short-wave infrared (SWIR), midwaveinfrared (MWIR), and/or long wave infrared (LWIR) wavelength ranges,including some overlapping ranges. These ranges correspond towavelengths of approximately 180-380 nm (UV), 380-700 nm (VIS), 700-2500nm (NIR), 850-1800 nm (SWIR), 650-1100 nm (MWIR), 400-1100 nm (VIS-NIR)and 1200-2450 nm (LWIR).

A LCTF employs birefringent retarders to distribute the light energy ofan input light signal over a range of polarization states. Thepolarization state of light emerging at the output of the LCTF is causedto vary as a function of wavelength due to differential retardation ofthe orthogonal components of light, contributed to by the birefringentretarders. The LCTF discriminates for wavelength-specific polarizationusing a polarizing filter at the output. The polarizing filter passesthe light components through the output that are rotationally aligned tothe polarizing filter. The LCTF is tuned by adjusting the birefringenceof the retarders so that a specific discrimination wavelength that isaligned to the output polarizing filter emerges in a plane polarizedstate. Other wavelengths that emerge in other polarization states and/oralignments are attenuated.

A highly discriminating spectral filter is possible using a sequence ofseveral birefringent retarders. The thicknesses, birefringences, andrelative rotation angles of the retarders are chosen to correspond tothe discrimination wavelength. More specifically, the input light signalto the filter becomes separated into orthogonal vector components,parallel to the respective ordinary and extraordinary axes of eachbirefringent retarder when encountered along the light transmission paththrough the filter. These separated vector components are differentiallyretarded due to the birefringence. Such differential retardation alsoamounts to a change in the polarization state. For a plane polarizedcomponent at the input to the filter, having a specific rotationalalignment at the input to the filter and at specific discriminationwavelengths, the light components that have been divided and subdividedall emerge from the filter in the same polarization state and alignment,namely plane polarized and in alignment with the selection polarizer,i.e., the polarizing filter, at the output.

A filter as described is sometimes termed an interference filter due tothe components being divided and subdivided from the input andinterfering positively at the output selection polarizer are thecomponents that are passed through the filter. Such filters aresometimes described with respect to a rotational twist in the planepolarization alignment of the discriminated component between the inputand the selection polarizer at the output.

There are several known configurations of spectral filters comprisingbirefringent retarders and such filters include, for example, Lyot,Solc, and Evans types. These filters can be constructed with fixed(non-tunable) birefringent crystals as retarders. A filter withretarders that are tuned in unison will permit adjustment of thebandpass wavelength. Tunable retarders can comprise liquid crystals orcomposite retarder elements, each comprising a fixed crystal and anoptically aligned liquid crystal.

The birefringences and rotation angles of the retarders are coordinatedsuch that each retarder contributes part of the necessary change inpolarization state to alter the polarization state of the passbandwavelength from an input reference angle to an output reference angle.The input reference angle may be, for example, 45° to the ordinary andextraordinary axes of a first retarder in the filter. The outputreference angle is the rotational alignment of the polarizing filter,i.e., “selection polarizer.”

A spectral filter may have a comb-shaped transmission characteristic.Increasing or decreasing the birefringence while tuning to select thediscrimination wavelength (or passband), stretches or compresses thecomb shape of the transmission characteristic along the wavelengthcoordinate axis.

If the input light is randomly polarized, the portion that is spectrallyfiltered is limited to the vector components of the input wavelengthsthat are parallel to one of the two orthogonal polarization componentsthat are present. Only light at the specific wavelength, and at a givenreference polarization alignment at the input, can emerge with apolarization angle aligned to the rotational alignment of the selectionpolarizer at the output. The light energy that is orthogonal to thereference alignment at the input, including light at the passbandwavelength, is substantially blocked.

Currently, tunable optical filter technology is limited to singlebandpass, low throughput operation and passes only one of two orthogonalcomponents of input light. The transmission ratio in the passband is ata maximum for incident light at the input to the LCTF that is aligned toa reference angle of the LCTF. Transmission is at a minimum for incidentlight energy at the input that is orthogonal to that reference angle. Ifthe input light in the passband is randomly polarized, the best possibletransmission ratio in the passband is fifty percent. In addition,multiple discrete bandpass measurements are required for tissue typediscrimination. The need for multiple measurements translates directlyinto overall measurement time.

Multivariate Optical Computing is an approach which utilizes acompressive sensing device, e.g. an optical computer, to analyzespectroscopic data as it is collected. Other approaches utilize hardcoated optical computing filters such as Multivariate Optical Elements(“MOEs”). MOEs are application-specific optical thin film filters thatare used in transmission and reflectance modes. The radiometric responseof a MOE-based instrument is proportional to the intended tissue type inan associated matrix. While compressive sensing holds potential fordecreasing measurement time, the use of MOEs has limitations. Forexample, MOEs are fixed and lack flexibility for adapting to differenttissue types.

Cancer is an enormous global health burden, accounting for one in everyeight deaths worldwide. A critical problem in cancer management is thelocal recurrence of disease, which is often a result of incompleteexcision of the tumor. Currently, tumor margins must be identifiedthrough histological evaluation of an affected tissue biopsypost-surgery. As such, approximately one in four patients who undergotumor resection surgery will require a follow-up operation in order tofully excise the malignant tissue. Recent efforts aimed towardssignificantly reducing the frequency of local recurrence have employeddiffuse reflectance, radiofrequency spectroscopy, and targetedfluorescence imaging. However, there remains an urgent need to develop ahighly specific and sensitive tool to detect features in biologicaltissues, including intraoperative real-time tumor margin detectionmethods that will reduce the risk of cancer recurrence and the need forsubsequent operations.

Current techniques for gross anatomic pathology require inspection by apathologist and are therefore inherently subjective. There exists a needfor a system and method that would enable objective analysis of organsamples and other biological tissues. It would also be advantageous ifsuch a system and method were designed as an intra-operative tool,providing both molecular and spatial information. There exists a needfor an adaptable filter that can be used to detect a wide variety oftissue types while reducing overall measurement time. It would beadvantageous if the filter could be incorporated into a system forbiomedical applications such as intraoperative applications.

SUMMARY

Some embodiments are, individually and collectively, directed devices,systems that include an intraoperative optical diagnostic deviceconfigured to detect features of a biological sample. The intraoperativeoptical diagnostic device may include an optical separator positioned toreceive interacted photons from the biological sample and configured toseparate the interacted photons into a first optical path and a secondoptical path; a first conformal filter positioned to receive interactedphotons from the first optical path, the first conformal filter havingone or more filter stages configured to filter the interacted photons inthe first optical path and generate a first filtered component; a secondconformal filter positioned to receive interacted photons from thesecond optical path, the second conformal filter having one or morefilter stages configured to filter the second optical component andgenerate a second filtered component; a controller operably connected tothe first conformal filter and the second conformal filter, thecontroller being configured to apply voltage to each of the one or morefilter stages of the first conformal filter and each of the one or morefilter stages of the second conformal filter; and one or more detectorspositioned to receive the first filtered component, the second filteredcomponent or combinations thereof, each of the one or more detectorsbeing configured to detect the first filtered component, the secondfiltered component, and combinations there and generate image data fromthe first filtered component, the second filtered component, orcombinations thereof. The systems and methods of various embodiments mayfurther include a processor operably connected to each of the one ormore detectors and the controller, the processor being configured toanalyze the image data and generate images related thereto, theprocessor further being capable of causing the controller toindividually apply voltage to each stage of each of the first conformalfilter and the second conformal thereby individually tuning the each ofthe first conformal filter and second conformal filter.

In some embodiments, the one or more filter stages of the firstconformal filter and the one or more filter stages of the secondconformal filter comprise a tunable filter. In certain embodiments, eachof the first conformal filter and second conformal filter mayindividually include one or more of a liquid crystal tunable filter, anacousto optical tunable filter, a Lyot liquid crystal tunable filter, anEvans Split-Element liquid crystal tunable filter, a Solc liquid crystaltunable filter, a Ferroelectric liquid crystal tunable filter, and aFabry Perot liquid crystal tunable filter. In particular embodiments,the each of the first conformal filter and second conformal filterindividually include a multi-conjugate tunable filter.

In some embodiments, the controller may be configured to apply one ormore voltages to each of the filter stages of the first conformal filterand to each of the filter stages of the second conformal filter whichcause the first conformal filter to conform to a spectral shapeassociated with a first analyte and the second conformal filter toconform to a spectral shape associated with a second analyte. The firstanalyte and the second analyte in such embodiments, can be the same, orthe first analyte and the second analyte can be different. In certainembodiments, a Look Up Table (“LUT”) may be in operable communicationwith the processor, and the LUT may include one or more voltagesassociated with each stage of the one or more stages of the firstconformal filter and each stage of the one or more stages of the secondconformal filter and each voltage may configure each stage of the firstconformal filter and each stage of the second conformal filter to aspectral shape associated with the one or more analytes. In certainembodiments, the controller may be configured to apply the one or morevoltages to the one or more stages of the first conformal filter and theone or more stages of the second formal filter while image data iscollected.

In various embodiments, the one or more detectors may include a firstdetector configured to detect the first filtered component and a seconddetector configured to detect the second filtered component. In otherembodiments, the one or more detectors may include one detectorconfigured to detect the first filtered component and the secondfiltered component. In some embodiments, the first filtered componentand the second filtered component are detected simultaneously, and inother embodiments, the first filtered component and the second filteredcomponent are detected sequentially.

The image data may include a first data set generated from the firstfiltered component and a second data second generated from the secondfiltered component. In some embodiments, the first test data set mayinclude a target analyte of the one or more analytes and the second dataset may represent a matrix including one or more non-target analytes.Each of the one or more test data sets can include one or more of a VISdata set, a NIR data set, and a SWIR data set.

In some embodiments, the devices and systems may further include one ormore of a robotic instrument and a laparoscopic instrument.

The devices, systems, and methods described above may be used todistinguish between different tissues. For example, in some embodiments,the one or more features of the biological tissue may include one ormore of an anatomical feature, a normal tissue, an abnormal tissue, atumor, a tumor margin, a large organ section and a surgical margin. Inparticular embodiments, the biological sample may include one or more ofkidney tissue, heart tissue, breast tissue, ovarian tissue, lung tissue,liver tissue, bladder tissue, intestinal tissue, stomach tissue, corneatissue, lens tissue, bone tissue, and skin tissue.

In certain embodiments, the devices and systems may further include anon-transitory storage medium in operable communication with theprocessor, and the storage medium may include one or more programminginstructions that, when executed, causes the processor to do thefollowing:

-   -   direct the controller to apply one or more voltages to the one        or more stages of the first conformal filter to tune the first        conformal filter to a first configuration;    -   direct the controller to apply one or more voltages to the one        or more stages of the second conformal filter to tune the second        conformal filter to a second configuration;    -   generate the one or more test data sets; and    -   analyze the one or more test data sets.

In some embodiments, the storage medium may further include one or moreprogramming instructions that, when executed, cause the processor to:

-   -   select the first configuration from a LUT comprising the one or        more analytes, wherein the LUT comprises one or more voltages        associated with the one or more stages of the first conformal        filter to configure the first conformal filter to a first        analyte; and    -   select the second configuration from a LUT comprising the one or        more analytes, wherein the LUT comprises one or more voltages        associated with the one or more stages of the second conformal        filter to configure the second conformal filter to a secon        analyte.    -   In such embodiments, the first configuration may be a        configuration for detecting one or more target analytes from the        one or more analytes and the second configuration may include a        configuration for detecting a matrix comprising one or more        non-target analytes from the one or more analytes. In particular        embodiments, the storage medium may further include instructions        that, when executed, cause the processor to apply one or more        chemometric techniques to the one or more test data sets.

Particular embodiments are directed to methods for detecting one or morefeatures of a biological tissue that include the steps of: separatinginteracted photons comprising photons that have interacted with one ormore analytes in the biological sample into a first optical componentand a second optical component; passing the first optical componentthrough a first conformal filter comprising one or more filter stagesand generating a first filtered component; passing the second opticalcomponent through a second conformal filter comprising one or morefilter stages and generating a second filtered component; applying oneor more voltages to the one or more stages of the first conformal filterand to the one or more stages of the second conformal filter; detectingthe first filtered component and the second filtered component andgenerating one or more test data sets; and analyzing the one or moretest data sets with a computer processor to detect the features of thebiological tissue.

In some embodiments, applying one or more voltages to the one or morefilter stages of the first conformal filter and to the one or morestages of the second conformal filter may configure the first conformalfilter to conform to a spectral shape associated with a first analyteand may configure the second conformal filter to conform to a spectralshape associated with a second analyte. In some embodiments, applyingthe one or more voltages, may further include referencing a LUTcomprising one or more voltages associated with each stage of the one ormore stages of the first conformal filter and each stage of the one ormore stages of the second conformal filter, wherein the one or morevoltages applied to the first conformal filter configures the firstconformal filter to a spectral shape of a first analyte and the one ormore voltages applied to each stage of the second conformal filterconfigures the second conformal filter to a spectral shape associatedwith second.

In various embodiments, the one or more features of the biologicaltissue may be one or more of an anatomical feature, a normal tissue, anabnormal tissue, a tumor, a tumor margin, a large organ section and asurgical margin. In some embodiments, the first analyte and the secondanalyte can be the same, and in other embodiments, the first analyte andthe second analyte may be different. In some embodiments, the firstfiltered component and the second filtered component may be detected bythe same detector, and in other embodiments, the filtered component andthe second filtered component may be detected by a plurality ofdetectors. In some embodiments, the first filtered component and thesecond filtered component may be detected simultaneously, and in otherembodiments, the first filtered component and the second filteredcomponent may be detected sequentially.

In certain embodiments, the one or more voltages can be applied to theone or more stages of the first conformal filter and to the one or morestages of the second conformal filter actively.

In some embodiments, the one or more test data sets may include a firsttest data set generated from the first conformal filter and a secondtest data set generated from the second conformal filter. In suchembodiments, the first data set may represent the one or more targetanalytes of the one or more analytes and the second data set mayrepresent a matrix comprising one or more non-target analytes of the oneor more analytes. In certain embodiments, the biological sample may beone or more of kidney tissue, heart tissue, breast tissue, ovariantissue, lung tissue, liver tissue, bladder tissue, intestinal tissue,stomach tissue, cornea tissue, lens tissue, bone tissue, and skintissue. In various embodiments, the one or more test data sets mayinclude one or more of a VIS data set, a NIR data set, and a SWIR dataset.

In some embodiments, the step of analyzing may further include applyingone or more optical computations to the one or more test data sets. Incertain embodiments, the optical computation may include one or more ofT1, T1−T2 and (T1−T2)/(T1+T2).

In some embodiments, the methods may further include:

-   -   directing the controller to apply the one or more voltages to        the one or more stages of the first conformal filter to tune the        first conformal filter to a first configuration; and    -   directing the controller to apply the one or more voltages to        the one or more stages of the second conformal filter to tune        the second conformal filter to a second configuration.

In certain embodiments, the method may further include:

-   -   selecting the first configuration from a LUT comprising the one        or more analytes, wherein the LUT comprises more or more        voltages associated with the one or more stages of the first        conformal filter to configure the first conformal filter to a        first analyte; and    -   selecting the second configuration by consulting a LUT        comprising the one or more analytes, wherein the LUT comprises        more or more voltages associated with the one or more stages of        the second conformal filter to configure the second conformal        filter to a second analyte.

In some embodiments, the first configuration may include a configurationfor detecting one or more target analytes from the one or more analytesand the second configuration comprises a configuration for detecting amatrix comprising one or more non-target analytes from the one or moreanalytes. In certain embodiments, the step of analyzing may furtherinclude applying one or more chemometric techniques to the one or moretest data sets.

BRIEF DESCRIPTION OF THE FIGURES

The file of this patent contains at least one drawing/photographexecuted in color. Copies of this patent with colordrawing(s)/photograph(s) will be provided by the Office upon request andpayment of the necessary fee.

The accompanying drawings, which are included to provide furtherunderstanding of the disclosure and are incorporated in and constitute apart of this specification illustrate embodiments of the disclosure, andtogether with the description, serve to explain the principles of thedisclosure.

FIG. 1 is a schematic representation of an intraoperative opticaldiagnostic device according to an embodiment;

FIG. 2 is a schematic representation of an intraoperative opticaldiagnostic device according to a second embodiment;

FIG. 3 is a schematic representation of a conformal filter according toan embodiment;

FIG. 4 is a schematic representation of a conformal filter according toa second embodiment;

FIG. 5 is a schematic representation of a conformal filter according toa third embodiment;

FIG. 6 is representative of the detection capabilities on a kidneysample according to an embodiment;

FIG. 6A is representative of the detection capabilities on a kidneysample according to an embodiment;

FIG. 6B is representative of a comparison discrete bandpass measurementsplot according to an embodiment;

FIG. 7 is representative of the detection capabilities on a kidneysample according to a second embodiment;

FIG. 7A is representative of a multivariate score image of a kidneyaccording to an embodiment;

FIG. 7B is representative of a univariate score image of a kidneyaccording to an embodiment;

FIG. 7C is representative of the Receiver Operator Characteristic (ROC)curve generated for each score image according to an embodiment;

FIG. 8 is illustrative of the detection capabilities according to anembodiment;

FIG. 8A is representative of a reflectance image according to anembodiment;

FIG. 8B is representative of a reflectance image according to anembodiment;

FIG. 8C is representative of a score image according to an embodiment;

FIG. 8D is representative of a detection image according to anembodiment;

FIG. 9 is illustrative of the detection capabilities according to asecond embodiment;

FIG. 9A is representative of a score image according to an embodiment;

FIG. 9B is representative of a probability distribution according to anembodiment;

FIG. 9C is representative of a ROC curve according to an embodiment;

FIG. 10 is illustrative of the enhanced contrast achieved according toan embodiment; and

FIG. 10A is representative of a brightfield image of an entire kidney,ureter and surrounding fat according to an embodiment;

FIG. 10B is representative of a reflectance image according to anembodiment;

FIG. 10C is representative of an acquired image according to anembodiment;

FIG. 10D is representative of an image according to an embodiment;

FIG. 11 is illustrative of improved contrast achieved on a kidney sampleaccording to an embodiment;

FIG. 11A is representative of a NIR image according to an embodiment;

FIG. 11B is representative of a contrast image according to anembodiment; and

FIG. 11C is representative of a contrast image according to anembodiment.

DETAILED DESCRIPTION

Reference will now be made in detail to the embodiments of the presentdisclosure, examples of which are illustrated in the accompanyingdrawings. Wherever possible, the same reference numbers will be usedthroughout the specification to refer to the same or like parts.

Unless defined otherwise, all technical and scientific terms have thesame meaning as is commonly understood by one of ordinary skill in theart to which the embodiments disclosed belongs.

As used herein, “a” or “an” means “at least one” or “one or more.”

As used herein, “about” means that the numerical value is approximateand small variations would not significantly affect the practice of thedisclosed embodiments. Where a numerical limitation is used, unlessindicated otherwise by the context, “about” means the numerical valuecan vary by ±10% and remain within the scope of the disclosedembodiments.

“Optional” or “optionally” may be taken to mean that the subsequentlydescribed structure, event or circumstance may or may not occur, andthat the description includes instances where the event occurs andinstances where it does not.

The term “tissue” refers to an aggregate of morphologically similarcells with associated intercellular matter that may act together toperform one or more specific functions in the body of an organismincluding a human. The term “tissue” also encompasses organs comprisingone or more tissue types.

Various embodiments of the invention are directed to intraoperativeoptical diagnostic devices and systems for detecting the features ofbiological samples that include interopertive optical diagnosticdevices. Further embodiments are directed to methods for using suchdevices and systems. The intraoperative optical diagnostic devices ofsuch embodiments are capable of detecting morphological and biochemicaldifferences in the biological samples that are not visually detectableand are unlikely to be detected using current standard devices andtechniques. For example, in certain embodiments, the intraoperativeoptical diagnostic devices and systems incorporating these devices canbe used to distinguish a particular tissue type from neighboring tissuesthereby delineating the margins between these tissues. In particularembodiments, the intraoperative optical diagnostic devices and systemsincorporating these devices can be used to distinguish healthy tissuefrom diseased tissue, and in some embodiments the diseased tissue may becancerous tissue or tumor. The use of these devices during surgery mayprovide the operating surgeon with real time visual information showingthe margins of the diseased tissue.

The intraoperative optical diagnostic devices of various embodiments mayat least include an optical separator positioned to receive lightreflected from the biological tissue (i.e., interacted photons, whichcan include photons reflected by a sample, photons scattered by asample, and photons emitted by a sample) and separate the interactedphotons into at least two optical paths. Although the devices of suchembodiments can include more than two optical paths, for simplicity suchembodiments are referred to as “dual polarization” devices. Each opticalpath may include one or more filters that reflect interacted photons ofparticular wavelengths removing them from the optical path and allowother interacted photons to pass through the filter generating filteredinteracted photons, i.e. a “filtered component.” In some embodiments,each optical path may terminate in a detector which is positioned toreceive and detect the filtered component. In other embodiments, asingle detector may be positioned to simultaneously receive and detectthe filtered components from each optical path. Thus, embodiments mayinclude one or more detectors depending on the configuration. Theintraoperative optical devices of such embodiments including one or moredetectors may further include a processor electronically connected tothe one or more detectors that receive data from the detector. Theprocessor may be configured to analyze the data and generate an image ofthe biological sample, and in certain embodiments, the image may clearlyshow the boundaries of different tissue types in the biological sample.

Schematics of examples of intraoperative optical diagnostic devices areprovided in FIG. 1 and FIG. 2. FIG. 1 represents a device having anoptical separator 11 positioned to receive light from a sample 10 andsplit the received light into two optical paths (illustrated by hashedlines). In particular embodiments, the optical separator 11 may be apolarizing beamsplitter that redirects received light along distinctorthogonal beam paths. Filters 12A, 12B are positioned along eachoptical path to receive and filter the split light. In the configurationof FIG. 1, after passing through the filter 12A, 12B, the filtered beamstravel along their respective optical paths to reflectors (e.g.,mirrors) 13A, 13B to a combiner 14 such as a polarizing cube orpolarizing beam splitter where the optical paths are combined anddirected toward a detector 15, which may include, among other things, alens 16. In some embodiments, the optical paths may be directed to thedetector 15 separately; however, the optical paths from opticalseparator 11 to the combiner 14 should be symmetrical to avoid, forexample, the need for corrective optics.

FIG. 2 is a schematic of another example of intraoperative opticaldiagnostic devices of the invention. In the configuration shown in FIG.2, two detectors 25A, 25B are illustrated. Like the configurationillustrated in FIG. 1, an optical separator 21 is positioned to receivelight from a sample 20 and split the received light into two opticalpaths (illustrated by hashed lines). Filters 22A, 22B are positionedalong each optical path to receive and filter the split light. Unlikethe configuration of FIG. 1, after passing through the filter 12A, 12B,each of the filtered beams travels along its respective optical path toan independent detector 25A, 25B, which can include a lens 26A, 26B, tocapture filtered signals from each filter 22A, 22B. In some embodiments,the two filtered signals may be detected simultaneously, which couldallow for real-time detection when displayed in a non-overlappingconfiguration (side-by-side, top to bottom, etc.). In other embodiments,the two filtered signals may be detected sequentially.

In some embodiments, the intraoperative optical diagnostic devices, suchas those illustrated in FIG. 1 and FIG. 2, may include anillumination/excitation source 17, 27, such as a spot light or laser. Inother embodiments, the source light may be a passive light source, forexample, in the case of intraoperative devices, lights used toilluminate an operating room or spotlights positioned by the operatingphysician or surgical assistant to illuminate the tissue for visualobservation. The illumination/excitation source 17, 27 may be positionedto illuminate the biological sample 10, 20 directly, or in someembodiments, the illumination/excitation source 17, 27 may direct light,for example, from an oblique angle to the biological sample 10, 20.Notably, although light irradiating the sample 10, 20, for example, by alaser, may be coherent, the light received from the sample 10, 20 (e.g.,emitted, scattered, and/or reflected light) and fed to the filters 12A,12B, 22A, 22B may not be coherent.

In some embodiments, the filters 12A, 12B, 22A, 22B may be tuned to afilter having a particular spectral shape. In other embodiments, thefilters 12A, 12B, 22A, 22B may be tuned between uses or while the deviceis in use. In such embodiments, the intraoperative optical diagnosticdevices may include one or more controllers 18, 28. The one or morecontrollers 18, 28 may be operably connected to each filter 12A, 12B,22A, 22B, and may be configured to tune each filter independently or inunison. Therefore, by appropriate control, the filters 12A, 12B, 22A,22B may be tuned to the same spectral shape or to two different spectralshapes at the same time. For example, one filter 12A, 22A may be tunedto a configuration for detecting a first tissue type, and the otherfilter 12B, 22B may be tuned to detect a second tissue type. In variousembodiments, the first tissue type may be healthy tissue, which can bereferred to as a “matrix.” The second tissue type may be diseasedtissue, such as a tumor, and the filter associated with the secondtissue type may be tuned or configured to detect a tissue typeassociated with the disease state. For example, the second tissue typemay be cancerous or tumor tissue which expresses a protein or contains atissue component that is not present in healthy tissue. The controller18, 28 may be programmable or implemented in software to allow a user toselectively tune each filters 12A, 12B, 22A, 22B.

The detectors 15, 25A, 25B of various embodiments may be any type ofdetector known in the art. For example, in some embodiments, eachdetector 15, 25A, 25B may be a charge coupled device (CCD), acomplementary metal-oxide-semiconductor (CMOS) detector, an indiumgallium arsenide detector, a platinum silicide detector, an indiumantimonide detector, a mercury cadmium telluride detector, or anycombination thereof. In certain embodiments, each detector 15, 25A, 25Bmay be a CCD or CMOS detector.

The intraoperative optical diagnostic devices described above mayinclude a processor or a means for connecting to a processor. In suchembodiments, the processor may operably connect to at least thedetectors 15, 25A, 25B, and in certain embodiments, the detectors 15,25A, 25B and the controller 18, 28. The processor may be configured toreceive data relating to the filtered light from each detector 15, 25A,25B and use this data to generate an image and display the image on adisplay device.

In some embodiments, the processor may generate a single image that isdisplayed on the display device, and in other embodiments, the processormay generate multiple images based on the data acquired from eachdetector 15, 25A, 25B. In still other embodiments, the device mayinclude a fast switching mechanism to switch between the two views (orspectral images) corresponding to spectral data collected by thedetector 15, 25A, 25B from each of the filters 12A, 12B, 22A, 22B. Whena single image is displayed, the image may be generated from spectraldata obtained from one filter 12A, 12B, 22A, 22B, or the spectral datamay be combined or overlaid into a single image, which may provideincreased contrast or intensity or provide a comparison. In otherembodiments, separate images corresponding with the data obtained fromeach filter 12A, 12B, 22A, 22B may be displayed side-by-side.

In some embodiments, the processor may be in communication with anon-transitory, computer readable storage medium containing a look-uptable (“LUT”). The LUT may include information that allows the filter tobe tuned to detect particular tissue types associated with particulardiseased states. For example, a LUT may include a number of voltagesthat when applied to a filter 12A, 12B, 22A, 22B allow the filter toproduce filtered light of a spectral shape associated with one or moretissue types related to various diseased states. In the case of amulti-stage filter, the LUT may include voltages that can be applied toeach stage in order to produce filtered light associated with tissuetypes related to various diseased states.

In embodiments including a LUT, the processor may acquire theappropriate information from the LUT based on user input or imageprocessing. The processor may then communicate this information to thecontroller 18, 28, which in turn applies the appropriate voltages toeach filter 12A, 12B, 22A, 22B or each stage in each filter. In someembodiments, this process may occur in or in near real time providingflexibility for detecting multiple tissue types of interest in near realtime. This may allow the user to modify or completely change thedisplayed image while the intraoperative optical diagnostic device is inuse.

Embodiments are not limited to particular filters. For example, eachfilter 12A, 12B, 22A, 22B may be a multi-conjugate liquid crystaltunable filter, an acousto-optical tunable filter, a Lyot liquid crystaltunable filter, an Evans split-element liquid crystal tunable filter, aSolc liquid crystal tunable filter, a ferroelectric liquid crystaltunable filter, or a Fabry Perot liquid crystal tunable filter, and insome embodiments, each optical path may include a combination of suchfilters. In certain embodiments, each filter 12A, 12B, 22A, 22B mayinclude a modified liquid crystal tunable filter and a liquid crystaltunable filter. In particular embodiments, each filter 12A, 12B, 22A,22B of the device may be independently tunable.

In certain embodiments, each filter 12A, 12B, 22A, 22B may independentlybe a conformal filter. The term “conformal filter” refers to filtersthat simultaneously transmit multiple passbands, i.e., spectral shapes.The use of conformal filters improves discrimination performance fortissue types by, for example, discriminating between a target tissuetype and background, and increases the throughput of a tunable filter,thereby, improving the speed of an analysis. The conformal filters,which are traditionally intended for single bandpass transmission, maybe tunable to enable tuning to a variety of different configurations. Anumber of filter types can be used as conformal filters and areencompassed by the filters 12A, 12B, 22A, 22B described above. Examplesof tunable filters that may be configured for use as a conformal filtermay include, but are not limited to, a liquid crystal tunable filter, anacoustic optical tunable filter, a Lyot liquid crystal tunable filter,an Evans Split-Element liquid crystal tunable filter, a Solc liquidcrystal tunable filter, a Ferroelectric liquid crystal tunable filter, aFabry Perot liquid crystal tunable filter, and combinations thereof.

In particular embodiments, the tunable filter may be a magneticallycoupled filter (MCF), which can include successive stages along anoptical path, and in some embodiments, each stage may be configured as aSolc filter. Angularly distributed retarder elements of equalbirefringence are stacked in each stage with a polarizer between stages.The retarders can include tunable (such as abutted liquid crystals),fixed and/or combined tunable and fixed birefringences. In someembodiments, the retarders may be quartz retarders. Although theretardations are equal within each stage, distinctly differentretardations may be used for two or more different stages. This causessome stages to pass narrow bandpass peaks and other stages to havewidely spaced bandpass peaks. The transmission functions of the serialstages are superimposed with selected tunable peaks coinciding. Theresulting conjugate filter has a high finesse ratio and good out of bandrejection. As discussed above, conformal filter configurations may bedetermined by consulting the LUT, which includes informationcorresponding with the conformal figure configuration necessary toobtain filtered light that can be used to detect various tissue types.The LUT may comprise at least one voltage associated with each stage ofthe tunable filter. These voltages may be such that when applied to theassociated stage, the tunable filter conforms to a spectral shapeassociated with the tissue type. LUTs may be modified, to provide theappropriate conformal filter configurations for detecting a variety ofdifferent tissue types.

In various embodiments, the conformal filters 12A, 12B, 22A, 22B may betuned to filter interacted photons that conform to the same spectralshapes. In other embodiments, the conformal filters 12A, 12B, 22A, 22Bmay be tuned to filter interacted photons that conform to differentspectral shapes. A system including conformal filters 12A, 12B, 22A, 22Btuned to filter different spectral shapes can be used to simultaneousanalyze a biological tissue for a plurality of tissue components ofinterest.

FIGS. 3-5 are schematics of conformal filters that can be incorporatedinto the intraoperative optical diagnostic devices of variousembodiments described above.

FIG. 3 shows a conformal filter 30 that includes a hot mirror 300 andmay be operably connected to a plurality of filter stages, such as afirst stage 310, a second stage 320, a third stage 330, and a fourthstage 340. Each stage 310, 320, 330, 340 is arranged in a Solcconfiguration including a polarizer 311, 321, 331, 341 upstream from acombination of liquid crystal cells 312, 322, 332, 342. In stages three330 and four 340, quartz retarders 333 and 343 are interspersed betweenthe liquid crystal cells of the combination of liquid crystal cells 332and 342. An input antireflective (AR) glass component 301 is disposedupstream of the first polarizer 311, and an output AR glass component302 is disposed downstream of an output polarizer 303. The conformalfilter 30 may further include a temperature sensor 350 for monitoringthe temperature of the filter. A graph showing the predicted percenttransmission (% T) as a function of wavelength (λ) of a filterconfigured 30 as described in FIG. 3 operating in both a bandpass and aconformal mode is provided in the inset graph 360.

FIG. 4 shows a conformal filter 40 having a similar configuration to theconformal filter 30 of FIG. 3 with the addition of an input polarizer404 upstream of the hot mirror 400. In some embodiments, the inputpolarizer 404 may be a mechanically rotatable polarizer or anelectronically tunable liquid crystal cell, and in certain embodiments,the input polarizer 404 may be mounted to a rotatable aperture forincreasing optical throughput. The input polarizer 404 may be tuned witheach individual filter stage 410, 420, 430, 440, or the input polarizer404 may be tuned simultaneously with all of the filter stages 410, 420,430, 440. In still other embodiments, the input polarizer 404 may betuned separately. In addition, the conformal filter 40 of FIG. 4 doesnot include retarders. Like the conformal filter 30 of FIG. 3, eachfilter stage 410, 420, 430, 440 may include polarizers 411, 421, 431,441 and liquid crystal cells 412, 422, 432, 442. An input antireflective(AR) glass component 401 may be positioned upstream of the first filterstage 410 polarizer 411, and an output AR glass component 402 may bepositioned downstream of an output polarizer 403. A graph showing thepredicted percent transmission (% T) as a function of wavelength (λ) ofa filter configured 40 as described in FIG. 4 operating in both abandpass and a conformal mode is provided in the inset graph 460.

In particular embodiments, tunable filters may be modified orspecifically designed so that selected individual stages of atraditional tunable filter include multiple, lower resolution liquidcrystal cells. Such a configuration is illustrated by FIG. 5, whichshows an conformal filter 50 having fewer stages 510, 520. Each filterstage 510, 520 includes a polarizer 511, 521 and combination of liquidcrystal cells 512, 522, and the second stage 520 includes quartzretarders 523 interspersed between the liquid crystal cells 522. As inthe conformal filters 30, 40 of FIG. 3 and FIG. 4, the conformal filter50 of FIG. 5 may also include an output polarizer 503. Other components,such as a hot mirror, input AR glass, output AR glass, input polarizers,and the like, not depicted in FIG. 5, may also be incorporated intoconformal filters such as the conformal filter 50 illustrated in FIG. 5.A graph showing the predicted percent transmission as a function ofwavelength (λ) of a conformal filter 50 configured as described in FIG.5 operating in conformal mode is provided in the inset graph 560.

The embodiments are not intended to be limited to the designs describedin FIG. 3-5. Recent advances in genomics and proteomics have identifieda large number of molecules and signaling pathways that couldpotentially promote or limit diseases such as cancer, atherosclerosis,and infectious disease. Due to the sensitivity of molecular imaging tosuch changes, tissue types associated with cancer and non-canceroushealthy tissue can be identified.

The processor can be configured in any way and can manipulate andanalyze the raw image data obtained from the one or more detectors inany way. In some embodiments, the processor may utilize MultivariateOptical Computing (MOC) techniques. Compressive sensing is the processin which a fully resolved waveform or image is reconstructed from asmall set of sparse measurements using the redundancy in informationacross the sampled signal similar to lossy compression algorithmsutilized for digital data storage. A fully expanded data set may becreated through the solution of an undetermined linear system, which isan equation where the compressive measurements collected are smallerthan the size of the original waveform or image. Compressivemeasurements may increase the rate at which image data is analyzed whilepreserving most of the original spectroscopic and spatial informationcontained in a molecular image collected over the full spectrum.Real-time Contrast Enhancement (RtCE) is the algorithmic optimization ofdual polarization conformal filter measurements designed to produce anoptical transmission function for analytical response. By employingconformal filter technology in conjunction with RtCE, fewer highthroughput measurements would be required to achieve tissue typespecificity such as tumor margin detection at a faster measurement timewhen compared to current imaging methods.

For example, as shown in FIG. 6B, in a conformal approach, fewer highthroughput measurements resulted in a faster measurement time comparedto current hyperspectral imaging (HSI) techniques. FIG. 6A shows abrightfield image and the resultant score image using current HSItechniques. FIG. 6B compares a discrete bandpass measurements plot,which contains more wavelength-measurements, compared to conformalmeasurements, which contain less wavelength-measurements. Both sets ofdata lead to the same results using partial least squares (PLS) andoptical regression methods. Thus, a highly informative detection canoccur when collecting fewer measurements, as in a conformal approach,than when using current HSI techniques and produce the same score image.

FIG. 7A shows a representative multivariate score image of a kidney thatwas generated through an applied classification algorithm based upon theresults of a partial least squares discriminate analysis (PLS-DA) ofspectra extracted from molecular images (full hyperspectral images) ofexcised kidneys. FIG. 7B shows a representative univariate score imageof kidney that was obtained by division of two frames extracted at twowavelengths (FIG. 7B). FIG. 7C shows the Receiver OperatorCharacteristic (ROC) curve generated from each score image. Multivariateanalysis yielded superior results as indicated by a higher area underthe ROC (AUROC) of the multivariate score image when compared to that ofthe univariate score imaging. While univariate analysis may drasticallyreduce the time for data collection and analysis, sensitivity andspecificity often suffer.

RtCE can be used to optimize a dual polarization conformal filter forhigh tissue type sensitivity and specificity by adjusting the voltageapplied to the stages of the conformal filters based on image dataobtained in real-time. In such embodiments, a measurement field of view(FOV) containing both tumor and non-tumor can be selected, and areference image can be collected. The user can then define the tolerancefor an intended tissue type and an associated figure of merit (FOM). Theuser defines an optical computation from a set of defined computationsfor the intended tissue type. The processor performs a non-linearoptimization process and iterations of this process are performed untilthe FOM is minimized to the defined tolerance.

In some embodiments, the system may further include a non-transitorystorage medium in operable communication with the processor. Thisstorage medium may include various operating systems and other computerprograms and hardware necessary to communicate with the controller andfilters. In certain embodiments, the storage medium may include one ormore programming instructions that, when executed, causes the processorto do the following:

-   -   (a) direct the controller to apply one or more voltages to the        one or more stages of the first conformal filter to tune the        first conformal filter to a first configuration;    -   (b) direct the controller to apply one or more voltages to the        one or more stages of the second conformal filter to tune the        second conformal filter to a second configuration;    -   (c) generate the one or more test data sets; and    -   (d) analyze the one or more test data sets.

In some embodiments, the storage medium further contains one or moreprogramming instructions that, when executed, cause the processor toselect the first configuration from a LUT comprising one or more firsttissue types, and select the second configuration from a LUT comprisingthe one or more second tissue types. In certain embodiments, the firstconfiguration for filtering photons that have interacted one or morefirst tissue types may be used to identify a target tissue, and thesecond configuration for filtering photons that have interacted with oneor more second tissue types may be used for identifying matrix, ornon-target tissue types. In yet other embodiments, the storage mediummay contain instructions that, when executed, cause the processor toapply one or more chemometric techniques to the image data. Of course,the storage medium may further contain any combination of theinstructions described above.

Other embodiments are directed to methods for detecting or imaging thefeatures of biological tissues using the devices and systems describedabove. In some embodiments, the methods may include the steps ofseparating photons that have interacted with biological tissues into afirst optical component and a second optical component, passing thefirst optical component through a first conformal filter having one ormore filter stages to generate a first filtered component; passing thesecond optical component through a second conformal filter having one ormore filter stages to generate a second filtered component, individuallyapplying voltages to each of the one or more stages of the firstconformal filter and separately to each of the one or more stages of thesecond conformal filter; generating image data from the first and secondfiltered components; and generating an image of the biological tissue inwhich a first tissue type and a second tissue types are distinguished.

In some embodiments, applying voltages to each of the one or more filterstages of the first conformal filter and to each of the one or morestages of the second conformal filter configures the first conformalfilter to conform to a spectral shape associated with the first tissuetype and configures the second conformal filter to conform to a spectralshape associated with the second tissue type. In certain embodiments,applying the voltages, further comprises referencing a LUT comprisingvoltages associated with a first tissue type or a second tissue typethat can be applied to each stage of the one or more stages of the firstconformal filter and each stage of the one or more stages of the secondconformal filter to identify the first tissue type or second tissuetype. The voltages cause the conformal filter to which the voltages areapplied to filter interacted photons that have interacted with a tissuecomponent, such as a protein, sugar, DNA, RNA, or other biologicalmolecule that is present in the target tissue but not present or presentat lower concentrations or quantities in the matrix, non-target tissue.The tissue component may be an analyte. In such embodiments, by applyingthe voltages, the first conformal filter may be configured to filter aspectral shape associated with a first tissue component in the targettissue, and the second conformal filter may be configured to filter aspectral shape associated with a second tissue component in the matrixor non-target tissue. In various embodiments, the voltages may beapplied actively, meaning that the voltages are applied and the filtersare tuned in real time during image data collection.

In some embodiments, the first and second tissue components may be thesame, and in other embodiments, the first and second tissue componentsmay be different. In particular embodiments, image data associated withthe first filtered component and the second filtered component may becollected by the same detector, and in other embodiments, image dataassociated with the first and second filtered components may becollected by different detectors. In certain embodiments, image dataassociated with the first and second filtered components may becollected by multiple detectors. The image data for the first and secondfiltered components can be collected simultaneously or sequentially, andin some embodiments, a method may allow for both simultaneous andsequential image data collection.

Embodiments are not limited to particular features that can bedistinguished in the images created by the methods described above. Forexample, the features of the biological tissue may include, but are notlimited to, anatomical features, normal tissue, abnormal tissue, tumors,tumor margins, large organ sections, surgical margins, and the like andcombinations thereof.

Image data associated with the first and second tissue types may beacquired simultaneously. For example, in some embodiments, first imagedata may be acquired from the first conformal filter, and second imagedata may be acquired from the second conformal filter. The first imagedata and the second image data may be acquired or collected individuallyin sequential acquisition processes. In other embodiments, the first andsecond image data sets can be acquired simultaneously by separatedetectors for each image data set or simultaneously by a singledetector. In such embodiments, the first image data set may be imagedata relating to a target tissue or a tissue component in a targettissue, and the second image data set may be image data relating tonon-target tissue or a tissue component associated with non-targettissue. In certain embodiments, the image data may include image datafrom any spectral band including the VIS, NIR, or SWIR, and the imagedata may include a VIS data set, a NIR data set, and a SWIR data set.

In particular embodiments, generating an image may include analyzing theimage data. In such embodiments, analyzing may include applying one ormore optical computations to the image data. In certain embodiments, theoptical computation may include, for example, T₁, T₁−T₂,(T₁−T₂)/(T₁+T₂), and combinations thereof. In still other embodiments,analyzing may further include applying one or more chemometrictechniques to the image data.

In various embodiments, the methods may further include directing thecontroller to apply a voltage to the one or more stages of the firstconformal filter to tune the first conformal filter to a firstconfiguration; and directing the controller to apply a voltage to theone or more stages of the second conformal filter to tune the secondconformal filter to a second configuration. In still other embodiments,the methods may include selecting the first configuration from a LUTcomprising the one or more tissue types, wherein the LUT comprises oneor more voltages associated with the one or more stages of the firstconformal filter to configure the first conformal filter to a firsttissue type; and selecting the second configuration by consulting a LUTcomprising the one or more tissue types, wherein the LUT comprises oneor more voltages associated with the one or more stages of the secondconformal filter to configure the second conformal filter to a secondtissue type.

All of the methods of the various embodiments can be incorporated intothe systems described above and may be incorporated into the computerreadable instructions available to the processor. As such, the methodsmay be used to distinguish and image any biological tissue such as, forexample, kidney tissue, heart tissue, breast tissue, ovarian tissue,lung tissue, liver tissue, bladder tissue, intestinal tissue, stomachtissue, cornea tissue, lens tissue, bone tissue, and skin tissue.

By exploiting these modalities, a device of the present disclosure holdspotential for use by surgeons to provide diagnostic information in realtime and without the use of reagents. With the employment of conformalfilter technology and dual polarization, simultaneous data acquisitionat two discrete wavelengths will result in faster data acquisition andhigher throughput. This holds potential for providing an intraoperative,label-free cancer margin detector that is capable of generatingdiagnostic information in real time which combines the high sensitivityand specificity of multivariate techniques with the rapid acquisitiontime of univariate techniques.

While the invention has been described in detail in reference tospecific embodiments thereof, it will be apparent to one skilled in theart that various changes and modifications can be made therein withoutdeparting from the spirit and scope of the embodiments. Additionally,while the examples provided herein related to specific tissue types, thepresent disclosure is not limited to these tissue types and may be usedto detect a wide variety of tissue types of interest. Thus, it isintended that the present disclosure cover the modifications andvariations of this disclosure provided they come within the scope thisapplication.

EXAMPLES Example 1

FIGS. 8 and 9 are illustrative of the detection capabilities of theintraoperative optical diagnostic devices and systems described above.The system used relies on a robust design algorithm in order to producean appropriate optical transmission function(s) for the intendedanalytical response as opposed to tuning to discrete wavelengths. As aresult of the large spectral bandpass of the conformal filter, itsoptical throughput, and thus the measured signal to noise ratio (SNR),is considerably higher than similar filters operated in a singlewavelength mode. In addition, the conformal filter approach requiresfewer measurements to achieve tissue type specificity resulting in afaster measurement time as compared to conventional HSI. Not only doesthe conformal approach provide better detection performance for thetarget tissue type (highest Area Under the ROC Curve over all methods),the detection is made faster and demonstrates excellent discriminationbetween “near neighbors,” i.e., tissue types with similar spectralfeatures.

A pig kidney with ureter attached is used to demonstrate technicalfeasibility of discriminating between different tissue types using theintraoperative optical diagnostic devices and systems described above.The ureter 801 was selected as the tissue type of interest, and theother anatomic features, such as normal renal parenchyma (NRP 802) andfat 803, were selected as matrix (i.e., background). The sample wasanalyzed using an experimental set up as illustrated in FIG. 1 in whicha quartz tungsten halogen lamp was used as an illumination source, thefilter was a MCF conformal filter, and the detector was a CCD camera.RtCE methodology was applied to the image data collected using thedevice described above. Two VIS/NIR reflectance images (FIG. 8A, B) weregenerated. The optical computation was applied, and a score image FIG.8C was generated. As illustrated in the detection image (FIG. 8D), theureter 804 was detected and distinguished from the majority of thebackground features.

FIG. 9 shows the statistical analysis of the score image reproduced asFIG. 9A. A probability distribution FIG. 9B, illustrates in-class v.out-of-class detections on a pixel-by-pixel basis. The ROC curve FIG. 9Cwas generated by applying a threshold to the probability distribution inFIG. 9B and illustrates the sensitivity and false positive resultsachieved. These results show that the intraoperative optical diagnosticdevices and systems described above are capable of distinguishingbetween tissue types with excellent sensitivity and are capable ofgenerating useful images showing tissue boundaries.

Example 2

FIG. 10 illustrates the enhanced contrast achieved by usingintraoperative optical diagnostic devices incorporating dualpolarization and conformal filters imaging a kidney and distinguishingbetween NRP, fat and ureter tissue. FIG. 10A shows a brightfield imageof the entire kidney, ureter 1001, and surrounding fat 1003. The boxindicates the region of interest from which the image data presented inFIGS. 10B-D were derived. FIG. 10B is an NIR reflectance image of theregion of interest. FIG. 10C is an image acquired using the dualpolarization confocal filter device configured as illustrated in FIG. 1.During data collection, one MCF confocal filter collected the image dataat 965 nm, and the second MCF confocal filter collected an image data at925 nm. The image in FIG. 10D was calculated by dividing the 965 nmimage data by the 925 nm image data. Gaussian blurring of this imagesmoothed the image. FIG. 10D shows the improved contrast between theureter 1001 and the NRP 1002 over the NIR and single frame dualpolarization images in FIG. 10B and FIG. 10C. This improved contrast wascreated in a very short acquisition time comparable to a univariatesystem.

Example 3

FIG. 11 provides another example of the improved contrast provided bythe intraoperative optical diagnostic devices incorporating dualpolarization and conformal filters imaging a kidney. FIG. 11A is a NIRimage of the region of interest. As illustrated in FIG. 11B and FIG.11C, contrast between the ureter 1101 and the NRP 1102 is dramaticallyimproved using the dual polarization conformal filter configurationdescribed in FIG. 1. In this case, image data was collected through twoMCF confocal filters at 740 nm and 930 nm. FIG. 11B is the resultantimage after dividing the 740 nm image by the 930 nm image, and FIG. 11Cis the divided image (FIG. 11B) after Gaussian blurring. These dataagain show the improved contrast of images acquired using the devicesand systems described above over images acquired using current NIRdevices.

What is claimed is:
 1. A system comprising: an intraoperative opticaldiagnostic device configured to detect features of a biological samplecomprising: an optical separator positioned to receive interactedphotons from the biological sample and configured to separate theinteracted photons into a first optical path and a second optical path;a first conformal filter positioned to receive interacted photons fromthe first optical path, the first conformal filter having one or morefilter stages configured to filter the interacted photons in the firstoptical path and generate a first filtered component; a second conformalfilter positioned to receive interacted photons from the second opticalpath, the second conformal filter having one or more filter stagesconfigured to filter the interacted photons in the second optical pathand generate a second filtered component; a controller in communicationwith the first conformal filter and the second conformal filter, thecontroller being configured to apply one or more voltages to each of theone or more filter stages of the first conformal filter which causes thefirst conformal filter to conform to a spectral shape associated with afirst analyte, and each of the one or more filter stages of the secondconformal filter which causes the second conformal filter to conform toa spectral shape associated with a second analyte; and one or moredetectors positioned to receive the first filtered component, the secondfiltered component or combinations thereof, each of the one or moredetectors being configured to detect the first filtered component, thesecond filtered component, and combinations there and generate imagedata from the first filtered component, the second filtered component,or combinations thereof; a processor connected to each of the one ormore detectors and the controller, the processor being configured toanalyze the image data and generate images related thereto, theprocessor further being configured to cause the controller toindividually apply voltage to each stage of each of the first conformalfilter and the second conformal thereby individually tuning the each ofthe first conformal filter and second conformal filter; and a Look UpTable (“LUT”) in communication with the processor, wherein the LUTcomprises the one or more voltages associated with each stage of the oneor more stages of the first conformal filter and each stage of the oneor more stages of the second conformal filter.
 2. The system accordingto claim 1, wherein the one or more filter stages of the first conformalfilter and the one or more filter stages of the second conformal filtercomprise a tunable filter.
 3. The system according to claim 1, whereineach of the first conformal filter and second conformal filterindividually comprise one or more of a liquid crystal tunable filter, anacousto optical tunable filter, a Lyot liquid crystal tunable filter, anEvans Split-Element liquid crystal tunable filter, a Solc liquid crystaltunable filter, a Ferroelectric liquid crystal tunable filter, and aFabry Perot liquid crystal tunable filter.
 4. The system according toclaim 1, wherein the each of the first conformal filter and secondconformal filter individually comprise a multi-conjugate tunable filter.5. The system according to claim 1, wherein the first analyte and thesecond analyte are the same.
 6. The system according to claim 1, whereinthe first analyte and the second analyte are different.
 7. The systemaccording to claim 1, wherein the one or more detectors comprise a firstdetector configured to detect the first filtered component and a seconddetector configured to detect the second filtered component.
 8. Thesystem according to claim 1, wherein the one or more detectors compriseone detector configured to detect the first filtered component and thesecond filtered component.
 9. The system according to claim 1, whereinthe first filtered component and the second filtered component aredetected simultaneously.
 10. The system according to claim 1, whereinthe first filtered component and the second filtered component aredetected sequentially.
 11. The system according to claim 1, wherein theimage data comprise a first data set generated from the first filteredcomponent and a second data set generated from the second filteredcomponent.
 12. The system according to claim 11, wherein the first dataset comprises a target analyte and the second data set represents amatrix comprising one or more non-target analytes.
 13. The systemaccording to claim 1, wherein the controller is configured to apply theone or more voltages to the one or more stages of the first conformalfilter and the one or more stages of the second conformal filter whileimage data is collected.
 14. The system according to claim 1, furthercomprising one or more of a robotic instrument and a laparoscopicinstrument.
 15. The system according to claim 1, wherein the one or morefeatures of the biological tissue comprise one or more of an anatomicalfeature, a normal tissue, an abnormal tissue, a tumor, a tumor margin, alarge organ section and a surgical margin.
 16. The system of claim 1,wherein the biological sample comprises one or more of kidney tissue,heart tissue, breast tissue, ovarian tissue, lung tissue, liver tissue,bladder tissue, intestinal tissue, stomach tissue, cornea tissue, lenstissue, bone tissue, and skin tissue.
 17. The system of claim 1, whereinone or more test data sets comprise one or more of a VIS data set, a NIRdata set, and a SWIR data set.
 18. The system of claim 1, furthercomprising a non-transitory storage medium in communication with theprocessor, wherein the storage medium comprises one or more programminginstructions that, when executed, causes the processor to do thefollowing: (a) direct the controller to apply one or more voltages tothe one or more stages of the first conformal filter to tune the firstconformal filter to a first configuration; (b) direct the controller toapply one or more voltages to the one or more stages of the secondconformal filter to tune the second conformal filter to a secondconfiguration; (c) generate one or more test data sets; and (d) analyzethe one or more test data sets.
 19. The system of claim 18, wherein thestorage medium further contains one or more programming instructionsthat, when executed, cause the processor to: select the firstconfiguration from a LUT comprising one or more analytes, wherein theLUT comprises one or more voltages associated with the one or morestages of the first conformal filter to configure the first conformalfilter to a first analyte; and select the second configuration from aLUT comprising the one or more analytes, wherein the LUT comprises oneor more voltages associated with the one or more stages of the secondconformal filter to configure the second conformal filter to a secondanalyte.
 20. The system of claim 19, wherein the first configurationcomprises a configuration for detecting one or more target analytes fromthe one or more analytes and the second configuration comprises aconfiguration for detecting a matrix comprising one or more non-targetanalytes from the one or more analytes.
 21. The system of claim 19,wherein the storage medium further contains instructions that, whenexecuted, cause the processor to apply one or more chemometrictechniques to the one or more test data sets.